2008年12月
A preferential attachment model with Poisson growth for scale-free networks
Annals of the Institute of Statistical Mathematics
- ,
- ,
- 巻
- 60
- 号
- 4
- 開始ページ
- 747
- 終了ページ
- 761
- 記述言語
- 英語
- 掲載種別
- 研究論文(学術雑誌)
- DOI
- 10.1007/s10463-008-0181-5
- 出版者・発行元
- SPRINGER HEIDELBERG
We propose a scale-free network model with a tunable power-law exponent. The Poisson growth model, as we call it, is an offshoot of the celebrated model of Barabási and Albert where a network is generated iteratively from a small seed network; at each step a node is added together with a number of incident edges preferentially attached to nodes already in the network. A key feature of our model is that the number of edges added at each step is a random variable with Poisson distribution, and, unlike the Barabási-Albert model where this quantity is fixed, it can generate any network. Our model is motivated by an application in Bayesian inference implemented as Markov chain Monte Carlo to estimate a network; for this purpose, we also give a formula for the probability of a network under our model. © 2008 The Institute of Statistical Mathematics, Tokyo.
- リンク情報
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- DOI
- https://doi.org/10.1007/s10463-008-0181-5
- arXiv
- http://arxiv.org/abs/arXiv:0801.2800
- Web of Science
- https://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=JSTA_CEL&SrcApp=J_Gate_JST&DestLinkType=FullRecord&KeyUT=WOS:000260635300003&DestApp=WOS_CPL
- Scopus
- https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=55549138366&origin=inward
- Scopus Citedby
- https://www.scopus.com/inward/citedby.uri?partnerID=HzOxMe3b&scp=55549138366&origin=inward
- ID情報
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- DOI : 10.1007/s10463-008-0181-5
- ISSN : 0020-3157
- eISSN : 1572-9052
- ORCIDのPut Code : 49219865
- arXiv ID : arXiv:0801.2800
- SCOPUS ID : 55549138366
- Web of Science ID : WOS:000260635300003